Model alignment method and device, equipment, storage medium and program product
By acquiring and comparing the texture maps of two three-dimensional models, detecting key points and establishing mapping relationships, the problem of inaccurate model alignment in the existing technology is solved, and a higher model alignment accuracy is achieved.
Patent Information
- Application Number
- CN202411505370.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-25
- Publication Date
- 2025-02-14
AI Technical Summary
The prior art cannot accurately align when dealing with three-dimensional models with inconsistent topology, especially when the point clouds of the face model are folded, resulting in poor accuracy of model alignment.
By obtaining the complete texture map of the two three-dimensional models, performing key point detection, we obtain the mapping relationship between the respective key points and the target points, and using this mapping relationship to align the two three-dimensional models.
This method can more accurately align the model, especially when the model has multi-layered sheet folds, improving the accuracy of the model alignment.
Smart Images
Figure CN119444962A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of communication technology, and in particular to a model alignment method, device, equipment, storage medium and program product. Background Art
[0002] One of the key steps in digital human modeling is to achieve the alignment relationship between two topologically inconsistent models.
[0003] For example, for the same person, multiple models of the person in different states are collected. For these models, each contains three core components: vertex data, such as the three-dimensional spatial coordinates of the vertex, UV data (such as the UV coordinates of each vertex), and UV map. Generally speaking, for models collected at different times, the number of vertex data, UV data, and UV map are different. Here, the number of vertex data, UV data, and UV map are called topological information.
[0004] In the prior art, the topological information aligned model is generally obtained by marking the face and performing retopological processing. However, this method cannot handle the situation where the face point cloud is folded, such as the eyelid area or the folded area of double-layer clothing, resulting in poor accuracy of model alignment. Summary of the invention
[0005] Embodiments of the present application provide a model alignment method, apparatus, device, storage medium, and program product to improve the accuracy of model alignment.
[0006] In a first aspect, an embodiment of the present application provides a model alignment method, comprising:
[0007] Obtaining a first complete texture map of the first three-dimensional model and a second complete texture map of the second three-dimensional model;
[0008] Performing key point detection on the first complete texture map and the second complete texture map respectively, to obtain a plurality of first key points of the first complete texture map and a plurality of second key points of the second complete texture map, wherein the plurality of first key points correspond to the plurality of second key points respectively;
[0009] Based on the first key point and the second key point, obtaining a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map;
[0010] The first three-dimensional model and the second three-dimensional model are aligned using the first mapping relationship.
[0011] In a second aspect, an embodiment of the present application further provides a model alignment device, comprising:
[0012] A first acquisition module, used to acquire a first complete texture map of the first three-dimensional model and a second complete texture map of the second three-dimensional model;
[0013] a first detection module, configured to perform key point detection on the first complete texture map and the second complete texture map, respectively, to obtain a plurality of first key points of the first complete texture map and a plurality of second key points of the second complete texture map, wherein the plurality of first key points correspond to the plurality of second key points respectively;
[0014] A second acquisition module, configured to obtain, based on the first key point and the second key point, a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map;
[0015] A first alignment module is configured to align the first three-dimensional model and the second three-dimensional model by using the first mapping relationship.
[0016] In a third aspect, an embodiment of the present application further provides a communication device, comprising: a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor implements the steps in the model alignment method as described above when executing the program.
[0017] In a fourth aspect, an embodiment of the present application further provides a readable storage medium, on which a program is stored, and when the program is executed by a processor, the steps in the model alignment method as described above are implemented.
[0018] In a fifth aspect, an embodiment of the present application further provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps in the model alignment method as described above.
[0019] In an embodiment of the present application, the model can be aligned according to a first mapping relationship between multiple first target points of a first complete texture map and multiple second target points of a second complete texture map. Since the first target point and the second target point are determined based on key points in the first complete texture map and the second complete texture map, the multiple first target points of the first complete texture map and the multiple second target points of the second complete texture map are more comprehensive. Furthermore, according to the first mapping relationship between the multiple first target points of the first complete texture map and the multiple second target points of the second complete texture map, the problem of not being able to accurately align the model when the model has multiple layers of fabric folded can be solved. Therefore, the accuracy of model alignment can be improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] Figure 1 It is one of the flow charts of the model alignment method provided in the embodiment of the present application;
[0021] Figure 2 and Figure 3 is a schematic diagram of a UV texture map of an embodiment of the present application;
[0022] Figure 4 and Figure 5 They are Figure 2 and Figure 3 The corresponding complete texture map;
[0023] Figure 6 and Figure 7 are schematic diagrams of key points of the first complete texture map and the second complete texture map, respectively;
[0024] Figure 8 and Fig. 9 They are Figure 6 and Figure 7 Schematic diagram after triangulation;
[0025] Fig.10 is a schematic diagram of determining a second target point in an embodiment of the present application;
[0026] Fig.11 is a structural diagram of a model alignment device provided in an embodiment of the present application;
[0027] Fig.12 It is a structural diagram of the communication device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0028] In the embodiments of the present application, the term "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.
[0029] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.
[0030] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0031] See also Figure 1 , Figure 1 is a flow chart of the model alignment method provided in the embodiment of the present application, such as Figure 1 As shown, the following steps are included:
[0032] Step 101: Obtain a first complete texture map of a first three-dimensional model and a second complete texture map of a second three-dimensional model.
[0033] In an embodiment of the present application, the UV texture maps of the initial model are spliced to obtain a complete texture map. The initial model includes at least a first three-dimensional model and a second three-dimensional model, the texture map of the first three-dimensional model is a first complete texture map, and the texture map of the second three-dimensional model is a second complete texture map. In this step, the UV texture maps of the first three-dimensional model are spliced to obtain the first complete texture map; the UV texture maps of the second three-dimensional model are spliced to obtain the second complete texture map.
[0034] UV texture mapping refers to the abbreviation of U and V texture mapping coordinates. The initial model can be a three-dimensional face model or the like.
[0035] In the embodiment of the present application, the UV texture map of the first 3D model and the second 3D model can be understood as a texture map with a broken texture. The first 3D model and the second 3D model do not necessarily completely overlap, and the second 3D model is obtained by deforming the first 3D model slightly. For example, when collecting facial expressions, the model M_t corresponding to time t and the model M_s corresponding to time s, the model M_t can be used as the first 3D model, and the model M_s can be used as the second 3D model. Figure 2 and Figure 3 As shown, a schematic diagram of UV texture mapping of the first three-dimensional model and the second three-dimensional model is shown. Figure 2 and Figure 3 As shown, the texture is messy and cannot represent a complete human face.
[0036] Here, the UV texture maps are spliced to obtain a complete texture map. For example, Figure 4 and Figure 5 They are Figure 2 and Figure 3 The corresponding complete texture map.
[0037] For example, in the process of forming a complete texture map, the target plane can be determined according to the coordinates of multiple initial key points in the initial model (such as a three-dimensional model), the initial model is divided into multiple facets, and the initial key points are the boundary vertices of the facets. After that, a key point set corresponding to each of the initial key points is obtained, and the key point set corresponding to each of the initial key points includes the coordinates of the initial key point and the initial key points in the neighborhood of the initial key point. Then, the Laplace coordinates of each of the initial key points on the target plane are determined according to each of the key point sets, and the texture map corresponding to each of the facets is inserted into the target plane according to a preset algorithm and the Laplace coordinates of each of the initial key points to obtain a two-dimensional texture map, which is a complete texture map.
[0038] The complete texture map retains the detailed information of the UV texture map, thereby ensuring the accuracy of the key points and target points obtained subsequently. The preset algorithm may be a triangular interpolation algorithm.
[0039] Step 102: perform key point detection on the first complete texture map and the second complete texture map respectively to obtain a plurality of first key points of the first complete texture map and a plurality of second key points of the second complete texture map, wherein the plurality of first key points correspond to the plurality of second key points respectively.
[0040] Here, key point detection can be performed on the first complete texture map and the second complete texture map by using face detection technology or model. Figure 6 and Figure 7 , which are schematic diagrams of the key points of the first complete texture map and the second complete texture map, respectively. Optionally, the two maps obtain key points in the same way, and this consistency is guaranteed by the key point detection algorithm (model). Generally speaking, for the same key point detection model, the number and semantics of key points detected on different images are fixed.
[0041] After the key points are determined, the mapping relationship between the first three-dimensional model and the second three-dimensional model can be obtained. Figure 5 and 6 As shown, Figure 5 and Figure 6 There are 118 key points in each. Figure 5 The key points in are mapped to Figure 6 The key points with the same semantics in the image are obtained, thereby obtaining the mapping relationship between the key points. In this step, the mapping relationship between the key points determined can be called a sparse mapping relationship.
[0042] Step 103: Based on the first key point and the second key point, obtain a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map.
[0043] In this step, a dense mapping relationship is formed through the mapping relationship between feature points (i.e., target points, which may also include key points). This step may include:
[0044] 1031. Divide the first complete texture map into a plurality of first triangular facets according to the plurality of first key points, and divide the second complete texture map into a plurality of second triangular facets according to the plurality of second key points, wherein the vertices of the first triangular facets are selected from the first key points, and the vertices of the second triangular facets are selected from the second key points.
[0045] The first complete texture map is divided into a plurality of first triangular facets in the same manner as the second complete texture map is divided into a plurality of second triangular facets. For example, the first complete texture map may be divided into a plurality of first triangular facets according to key points of the first complete texture map by a triangulation algorithm, and the second complete texture map may be divided into a plurality of second triangular facets according to key points of the second complete texture map by a triangulation algorithm.
[0046] The triangulation algorithm may be, for example, a Delaunay triangulation algorithm. Figure 8 and Fig. 9 As shown, they are Figure 6 and Figure 7 Schematic diagram after triangulation. In this way, it can be ensured that the triangular facets do not overlap each other and that key points are not missed.
[0047] 1032. Determine a corresponding second target point of each first target point of each first triangular facet in a second triangular facet corresponding to the first triangular facet, and obtain a mapping relationship between each first target point and the second target point.
[0048] Since the mapping relationship between key points has been established, the purpose here is to establish a mapping relationship between the points of the triangle patch of the first complete texture map and the points of a certain triangle patch of the second complete texture map, and the two triangle patches are connected through the above sparse mapping relationship. In other words, the three vertices of the first triangle patch and the three vertices of the second triangle patch are connected through the above sparse mapping relationship.
[0049] Here, interpolation calculation can be performed based on the UV coordinates of the three vertices of the first triangular patch to obtain the first interpolation coefficient and the second interpolation coefficient, and the UV coordinates of the first target point can be converted according to the UV coordinates of the three vertices of the second triangular patch, the first interpolation coefficient, and the second interpolation coefficient to obtain the coordinates of the second target point. The first target point is any feature point of the first triangular patch, that is, the first target point can include the vertices of the first triangular patch and / or points within the first triangular patch, and the second target point can include the vertices of the second triangular patch and / or points within the first triangular patch.
[0050] The above interpolation calculation can be realized by triangular interpolation, thin plate spline interpolation and other methods.
[0051] like Fig.10 As shown, the three vertices of the first triangular patch are P0, P1 and P2 respectively; through the aforementioned sparse mapping relationship, the three vertices of the corresponding second patch are F(P0), F(P1), and F(P2), and F() represents the sparse mapping relationship. For point P in the first triangular patch, the goal is to find the corresponding point F(P) of point P in the second patch. Below, taking the triangular interpolation algorithm as an example, we will describe how to determine F(P).
[0052] Assume that the UV coordinates of the three vertices of the first triangle are {P0 = (x0, y0), P1 = (x1, y1), P2 = (x2, y2)}, Pi∈R 2 , R represents a real number, i = 0, 1, 2. That is, the triangle is written in its own local coordinate system, which is independent of the choice of coordinate system. In the embodiment of the present application, the vector is represented as a column vector. After a deformation F: {P0, P1, P2} → R 2 Afterwards, the three vertices of the triangle patch become {F(P0) = (u0, v0), F(P1) = (u1, v1), F(P2) = (u2, v2)}. Note that the domain of the deformation F at this time is only the three vertices of the triangle patch.
[0053] For any point P = (x, y) ∈ R inside a non-degenerate triangle 2 , there exists a unique coordinate function λi:R 2 →R, i=1,2, such that:
[0054] P = P0 + λ1(P )(P1 - P0) + λ2(P )(P2 - P0) (1)
[0055] Assumption of linear deformation (triangular interpolation): The domain of the linear deformation F can be extended to the edge and interior of the entire triangle in the following way (in fact, it can be extended to the entire R 2). In the absence of ambiguity, the linear deformation with the extended domain is still recorded as F:R 2 →R 2 , P = (x, y) → F (P) = (u, v), the point P is deformed to:
[0056] F(P)=F(P0)+λ1(P)(F(P1)-F(P0))+λ2(P)(F(P2)-F(P0))(2)
[0057] The coordinate function is determined by the following relationship:
[0058] Given the vertices {P0, P1, P2} of a non-degenerate triangle and any point P within the triangle, (1) can be expressed as:
[0059]
[0060] Since the triangle patch is non-degenerate, the inverse of the matrix (P1-P0, P2-P0) exists.
[0061]
[0062] in,
[0063] Substituting (6) into (2) we get:
[0064]
[0065] Here, the coordinates of F(P) can be obtained by the above formulas (6) and (2). Thus, the second target point F(P) corresponding to point P is determined.
[0066] For each first target point in the first triangular patch, the corresponding second target point can be found in the second triangular patch in the above manner. Similarly, for other triangular patches, the second target point of each first target point in the corresponding triangular patch can also be determined. Thus, a mapping relationship between each first target point and the corresponding second target point is formed. At the same time, the mapping relationship can also include a mapping relationship between the vertices of the triangular patches.
[0067] 1033. Obtain the first mapping relationship according to the mapping relationship between each of the first target points and the corresponding second target point.
[0068] In the embodiment of the present application, interpolation is performed on the basis of the complete texture map to obtain the first mapping relationship, thereby avoiding edge problems when using fragmented texture maps for interpolation and improving the accuracy of model alignment.
[0069] Step 104: Align the first three-dimensional model and the second three-dimensional model using the first mapping relationship.
[0070] In an embodiment of the present application, the model can be aligned according to a first mapping relationship between multiple first target points of a first complete texture map and multiple second target points of a second complete texture map. Since the first target point and the second target point are determined based on key points in the first complete texture map and the second complete texture map, the multiple first target points of the first complete texture map and the multiple second target points of the second complete texture map are more comprehensive. Furthermore, according to the first mapping relationship between the multiple first target points of the first complete texture map and the multiple second target points of the second complete texture map, the problem of not being able to accurately align the model when the model has multiple layers of fabric folded can be solved. Therefore, the accuracy of model alignment can be improved.
[0071] See also Fig.11 , Fig.11 is a structural diagram of a model alignment device provided in an embodiment of the present application. Fig.11 As shown, the model alignment device includes:
[0072] A first acquisition module 1101 is used to acquire a first complete texture map of a first three-dimensional model and a second complete texture map of a second three-dimensional model;
[0073] A first detection module 1102 is used to perform key point detection on the first complete texture map and the second complete texture map respectively, to obtain a plurality of first key points of the first complete texture map and a plurality of second key points of the second complete texture map, wherein the plurality of first key points correspond to the plurality of second key points respectively;
[0074] A second acquisition module 1103, configured to obtain a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map based on the first key point and the second key point;
[0075] The first alignment module 1104 is configured to align the first three-dimensional model and the second three-dimensional model by using the first mapping relationship.
[0076] Wherein, the second acquisition module 1103 includes:
[0077] A first division submodule, configured to divide the first complete texture map into a plurality of first triangular facets according to the plurality of first key points, and to divide the second complete texture map into a plurality of second triangular facets according to the plurality of second key points, wherein the vertices of the first triangular facets are selected from the first key points, and the vertices of the second triangular facets are selected from the second key points;
[0078] A first determination submodule, configured to determine a corresponding second target point of each first target point of each first triangular facet in a second triangular facet corresponding to the first triangular facet, and to obtain a mapping relationship between each first target point and the second target point;
[0079] The second determining submodule is used to obtain the first mapping relationship according to the mapping relationship between each of the first target points and the corresponding second target point.
[0080] Optionally, the first determining submodule is further used to:
[0081] Performing interpolation calculation based on the UV coordinates of the three vertices of the first triangular face to obtain a first interpolation coefficient and a second interpolation coefficient;
[0082] The UV coordinates of the first target point are converted according to the UV coordinates of the three vertices of the second triangle patch, the first interpolation coefficient, and the second interpolation coefficient to obtain the coordinates of the second target point.
[0083] Optionally, the first division submodule is further used to:
[0084] Dividing the first complete texture map into a plurality of first triangular facets according to key points of the first complete texture map by a triangulation algorithm; and
[0085] The second complete texture map is divided into a plurality of second triangular facets according to the key points of the second complete texture map by using a triangulation algorithm.
[0086] Optionally, the first detection module 1102 is further used to perform key point detection on the first complete texture map and the second complete texture map respectively using a facial key point detection model to obtain key points of the first complete texture map and the second complete texture map.
[0087] Optionally, the first acquisition module 1101 is further used for:
[0088] splicing the UV texture map of the first three-dimensional model to obtain the first complete texture map;
[0089] The UV texture maps of the second three-dimensional model are spliced to obtain the second complete texture map.
[0090] The device provided in the embodiment of the present application can execute the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.
[0091] It should be noted that the division of units in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0092] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.
[0093] See also Fig.12 An embodiment of the present application provides a communication device, including: a memory 1201, a processor 1202, and a program stored in the memory 1201 and executable on the processor 1202; the processor 1202 is used to read the program in the memory 1201 to implement the steps in the model alignment method described above.
[0094] The embodiment of the present application also provides a readable storage medium, on which a program is stored, and when the program is executed by the processor, each process of the above-mentioned model alignment method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. Among them, the readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)), etc.
[0095] The embodiment of the present application also provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the various processes of the above-mentioned model alignment method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, they are not repeated here.
[0096] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.
[0097] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, disk, CD), and includes a number of instructions for a terminal (which can be a mobile phone, computer, server, air conditioner, or network equipment, etc.) to execute the methods described in each embodiment of the present application.
[0098] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.
Claims
1. A model alignment method, characterized in that: include: Obtaining a first complete texture map of the first three-dimensional model and a second complete texture map of the second three-dimensional model; Performing key point detection on the first complete texture map and the second complete texture map respectively, to obtain a plurality of first key points of the first complete texture map and a plurality of second key points of the second complete texture map, wherein the plurality of first key points correspond to the plurality of second key points respectively; Based on the first key point and the second key point, obtaining a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map; The first three-dimensional model and the second three-dimensional model are aligned using the first mapping relationship.
2. The method according to claim 1, characterized in that The obtaining, based on the first key point and the second key point, a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map comprises: Dividing the first complete texture map into a plurality of first triangular facets according to the plurality of first key points, and dividing the second complete texture map into a plurality of second triangular facets according to the plurality of second key points, wherein the vertices of the first triangular facets are selected from the first key points, and the vertices of the second triangular facets are selected from the second key points; Determine a corresponding second target point of each first target point of each first triangular facet in a second triangular facet corresponding to the first triangular facet, and obtain a mapping relationship between each first target point and the second target point; The first mapping relationship is obtained according to the mapping relationship between each of the first target points and the corresponding second target point.
3. The method according to claim 2, characterized in that Determining a corresponding second target point of each first target point of each first triangular facet in a second triangular facet corresponding to the first triangular facet comprises: Performing interpolation calculation based on the UV coordinates of the three vertices of the first triangular face to obtain a first interpolation coefficient and a second interpolation coefficient; The UV coordinates of the first target point are converted according to the UV coordinates of the three vertices of the second triangle patch, the first interpolation coefficient, and the second interpolation coefficient to obtain the coordinates of the second target point.
4. The method according to claim 2, characterized in that: The step of dividing the first complete texture map into a plurality of first triangular facets according to the plurality of first key points, and dividing the second complete texture map into a plurality of second triangular facets according to the plurality of second key points, comprises: Dividing the first complete texture map into a plurality of first triangular facets according to key points of the first complete texture map by a triangulation algorithm; and The second complete texture map is divided into a plurality of second triangular facets according to the key points of the second complete texture map by using a triangulation algorithm.
5. The method according to claim 1, characterized in that The performing key point detection on the first complete texture map and the second complete texture map respectively includes: The facial key point detection model is used to perform key point detection on the first complete texture map and the second complete texture map respectively to obtain key points of the first complete texture map and the second complete texture map.
6. The method according to claim 1, characterized in that The step of obtaining a first complete texture map of the first three-dimensional model and a second complete texture map of the second three-dimensional model includes: splicing the UV texture map of the first three-dimensional model to obtain the first complete texture map; The UV texture maps of the second three-dimensional model are spliced to obtain the second complete texture map.
7. A model alignment device, characterized in that: include: A first acquisition module, used to acquire a first complete texture map of the first three-dimensional model and a second complete texture map of the second three-dimensional model; a first detection module, configured to perform key point detection on the first complete texture map and the second complete texture map, respectively, to obtain a plurality of first key points of the first complete texture map and a plurality of second key points of the second complete texture map, wherein the plurality of first key points correspond to the plurality of second key points respectively; A second acquisition module, configured to obtain, based on the first key point and the second key point, a first mapping relationship between a plurality of first target points of the first complete texture map and a plurality of second target points of the second complete texture map; A first alignment module is configured to align the first three-dimensional model and the second three-dimensional model by using the first mapping relationship.
8. A communication device, comprising: A memory, a processor, and a program stored in the memory and executable on the processor; wherein the processor is used to read the program in the memory to implement the steps in the model alignment method as described in any one of claims 1 to 6.
9. A computer-readable storage medium for storing a program, characterized in that: When the program is executed by a processor, the steps in the model alignment method according to any one of claims 1 to 6 are implemented.
10. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps in the model alignment method according to any one of claims 1 to 6.